Instructions to use hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech") model = AutoModelForTextToWaveform.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech: direct link, hf CLI and curl.
- Browser
- Download file 231 Bytes
-
https://huggingface.co/hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech/resolve/aa7bc029005fdd080a72a58d321edba33fdfef4e/preprocessor_config.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech@aa7bc029005fdd080a72a58d321edba33fdfef4e/preprocessor_config.json
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curl -L -o preprocessor_config.json https://huggingface.co/hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToSpeech/resolve/aa7bc029005fdd080a72a58d321edba33fdfef4e/preprocessor_config.json
231 Bytes
| { | |
| "feature_extractor_type": "SeamlessM4TFeatureExtractor", | |
| "feature_size": 80, | |
| "num_mel_bins": 80, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000, | |
| "stride": 2 | |
| } | |